released swarm algorithms techreport

README.textile

@@ -64,6 +64,7 @@ h3. Technical Reports
 * Jason Brownlee. "Particle Swarm Optimization":http://github.com/jbrownlee/CleverAlgorithms/raw/master/workspace/release/techreport-20101114b-1.pdf. Technical Report CA-TR-20101114b-1, The Clever Algorithms Project http://www.CleverAlgorithms.com, November 2010.
 * Jason Brownlee. "Ant System":http://github.com/jbrownlee/CleverAlgorithms/raw/master/workspace/release/techreport-20101115-1.pdf. Technical Report CA-TR-20101115-1, The Clever Algorithms Project http://www.CleverAlgorithms.com, November 2010.
 * Jason Brownlee. "Ant Colony System":http://github.com/jbrownlee/CleverAlgorithms/raw/master/workspace/release/techreport-20101115a-1.pdf. Technical Report CA-TR-20101115a-1, The Clever Algorithms Project http://www.CleverAlgorithms.com, November 2010.
+* Jason Brownlee. "Swarm Algorithms":http://github.com/jbrownlee/CleverAlgorithms/raw/master/workspace/release/techreport-20101115b-1.pdf. Technical Report CA-TR-20101115b-1, The Clever Algorithms Project http://www.CleverAlgorithms.com, November 2010.
 * ...
 
 h3. Software

workspace/40-swarm-algorithms/techreport-20101115b.tex

@@ -72,7 +72,7 @@ \subsection{Background}
 
 % Immune
 \subsubsection{Swarm Intelligence}
-Swarm intelligence is the study of computational systems inspired by the collective intelligence that emerges through the cooperation of large numbers of homogeneous agents in the environment. Examples include schools of fish, flocks of birds, and colonies of ants. Such intelligence is decentralized, self-organizing and distributed through out an environment and in nature is commonly used to solve problems such as effective foraging for food, prey evading, or colony re-location. The information is typically stored throughout the participating homogeneous agents, or is stored or communicated in the environment itself such as through the use of pheromones in ants, dancing in bees, and proximity in fish and birds.
+Swarm intelligence is the study of computational systems inspired by the collective intelligence that emerges through the cooperation of large numbers of homogeneous agents in the environment. Examples include schools of fish, flocks of birds, and colonies of ants. Such intelligence is decentralized, self-organizing and distributed through out an environment. In nature such systems are commonly used to solve problems such as effective foraging for food, prey evading, or colony re-location. The information is typically stored throughout the participating homogeneous agents, or is stored or communicated in the environment itself such as through the use of pheromones in ants, dancing in bees, and proximity in fish and birds.
 
 The paradigm consists of two dominant sub-fields (1) \emph{Ant Colony Optimization} that investigates probabilistic algorithms inspired by the stigmergy and foraging behavior of ants, and (2) \emph{Particle Swarm Optimization} that investigates probabilistic algorithms inspired by the flocking, schooling and herding. Like evolutionary computation, swarm intelligences are considered adaptive strategies and are typically applied to search and optimization domains.
 
@@ -87,7 +87,7 @@ \subsubsection{References}
 \subsection{Described Algorithms}
 \label{subsec:algorithms}
 % overview
-This section lists the immune algorithms currently described for inclusion in the Clever Algorithms project. It is proposed that these algorithms will collectively comprise a chapter on `Swarm Algorithms' in the Clever Algorithms book. 
+This section lists the swarm algorithms currently described for inclusion in the Clever Algorithms project. It is proposed that these algorithms will collectively comprise a chapter on `Swarm Algorithms' in the Clever Algorithms book. 
 
 \begin{enumerate}
 	\item \textbf{Particle Swarm Optimization}: \cite{Brownlee2010ac}
@@ -103,9 +103,9 @@ \section{Extensions}
 There are other algorithms and classes of algorithm that were not described from the field of Swarm Intelligence. Some areas that may be considered for algorithm description in follow up works include:
 
 \begin{itemize}
-	\item \textbf{Social Insects}: There are algorithms inspired by other social insects besides ants, such as: bees, wasps, fireflies, and termites. 
+	\item \textbf{Social Insects}: There are algorithms inspired by other social insects besides ants, such as: bees, wasps, fireflies, and termites.
 	\item \textbf{Bacteria}: Another related area is that of algorithms inspired by the social-like properties of some bacteria which may be considered a swarm intelligence.
-	\item \textbf{Cellular Systems}: There are algorithms inspired by social-like mechanisms in cellular systems like the immune system and cancers.  
+	\item \textbf{Cellular Systems}: There are algorithms inspired by social-like mechanisms in cellular systems like the immune system and cancers.
 \end{itemize}
 
 %